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A new prediction model for left ventricular systolic function recovery after catheter ablation of atrial fibrillation in patients with heart failure The ANTWOORD Study

Journal Contribution - Journal Article

Background: in patients with heart failure (HF) and atrial fibrillation (AF), AF ablation improves left ventricular ejection fraction (LVEF), along with prognosis, in a variable percentage of patients. We aimed to investigate the predictors of LVEF recovery after AF ablation and to develop a prediction model for individualized assessment. Methods: we conducted an observational, retrospective, single-centre study on 111 consecutive patients with AF and HF with impaired LVEF (<50%) undergoing ablation. Patients were divided into Responder vs. Non-Responder according to the "Universal definition of HF". Clinical predictors were evaluated by multivariate logistic regression analysis and cross-validation technique. Independent predictors were used to build an internally validated prediction model. Results: Responders (54%) had significantly shorter QRS duration and less dilated left atrium. Persistent AF and absence of a known etiology were more frequent among Responders. AF recurrence was similar between the two groups (p = 0.2), but the percentage of patient with persistent AF after ablation was significantly lower among Responders (p < 0.001). Absence of known etiology, presence of persistent AF, left atrial volume index<50 mL/m(2), and QRS < 120 msec were independent predictors of LVEF recovery and composed the Score (AUC 0.93;95% CI 0.88-0.98-p < 0.001). Patients with Score <= 1 had 90% likelihood of LVEF recovery, compared to 5% in patients with 3-6. Conclusions: Patients with wide QRS, known HF etiology, dilated left atrium, and paroxysmal AF were less likely to recover LVEF after AF ablation. A new score system based on the above-mentioned parameters adequately predicts LVEF recovery after AF ablation. These results warrant confirmation and prospective validation.
Journal: International journal of cardiology
ISSN: 0167-5273
Volume: 358
Pages: 45 - 50
Publication year:2022
Keywords:A1 Journal article
Accessibility:Closed